| 引用本文: | 管业鹏, 顾伟康.提取二维图像特征点阈值的自动确定[J].控制理论与应用,2005,22(3):381~385.[点击复制] |
| GUAN Ye-peng, GU Wei-kang.Automatic threshold confirmation for extracting feature points in 2-dimensional images[J].Control Theory and Technology,2005,22(3):381~385.[点击复制] |
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| 提取二维图像特征点阈值的自动确定 |
| Automatic threshold confirmation for extracting feature points in 2-dimensional images |
| 摘要点击 1270 全文点击 1133 投稿时间：2003-09-17 修订日期：2004-05-21 |
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| DOI编号 10.7641/j.issn.1000-8152.2005.3.008 |
| 2005,22(3):381-385 |
| 中文关键词 概率论 标准差 异常 灰度 阈值 |
| 英文关键词 probability theory standard deviation abnormity gray-level threshold value |
| 基金项目 上海市教委曙光项目资助(04CX72). |
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| 中文摘要 |
| 根据灰度图像中噪声与特征点在灰度曲面中呈现出的不同分布特征,提出了对抽样区域的象素灰度进行偏差迭代运算以确定特征点象素,采用计算算术平均的办法确定阈值.采用该方法确定阈值,避免了提取图像特征点时,根据被处理图像的一些先验信息,利用试探方法确定阈值的局限性.通过对不同自然二维图像的特征点提取,证明了文中所确定的阈值是合理、有效的. |
| 英文摘要 |
| According to the different distributions on the gray surface between noise and feature points,the location of feature point was located by recursively computing deviation of gray-level within the sampled area.The threshold value was ascertained by the arithmetical average method.The limitation to confirm threshold value with tentative method and a priori information on processing image would be avoided.Experimental results of extracting feature points on different natural 2-D images proved that the threshold value determined was reasonable and effective. |